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The book provides an overview of the state-of-the-art of map construction algorithms, which use tracking data in the form of trajectories to generate vector maps. The most common trajectory type is GPS-based trajectories. It introduces three emerging algorithmic categories, outlines their general algorithmic ideas, and discusses three representative algorithms in greater detail. To quantify map construction algorithms, the authors include specific datasets and evaluation measures. The datasets, source code of map construction algorithms and evaluation measures are publicly available on http://www.mapconstruction.org. The web site serves as a repository for map construction data and algorithms and researchers can contribute by uploading their own code and benchmark data. Map Construction Algorithms is an excellent resource for professionals working in computational geometry, spatial databases, and GIS. Advanced-level students studying computer science, geography and mathematics will also find this book a useful tool.
Analyzing and mining various kinds of geo-referenced data is important in many application areas. We use two types of data: geo-referenced trajectories, such as vehicular tracking data, as well as geo-referenced graph data, such as street maps. This dissertation consists of two main parts. In the first part, we consider the problem of constructing street maps from geo-referenced trajectories: Given a set of trajectories in the plane, compute a street-map that represents all trajectories in the set. In this part, we have two main contributions. First, we present a scalable incremental algorithm that is based on partial matching of the trajectories to the graph. For the partial matching we introduce a new variant of partial Fréchet distance. We use minimum-link paths to reduce the complexity of the generated map. We provide quality guarantees and experimental results based on both real and synthetic data. We further present two multi-thresholding techniques for density-based map construction algorithms. Multi-thresholding is necessary because some streets are travelled more heavily than other streets (highways vs. neighborhood streets), which results in different sampling densities, and thus, one threshold fails to capture all the streets. We present a new thresholding technique that uses persistent homology combined with statistical analysis to determine a small set of thresholds that captures all or most of the significant topological features. We also formalize the selection of thresholds in a density-based map construction algorithm for different variants of uniform sampling. In part two of the dissertation, we consider the map comparison problem: Given two street-maps embedded in space, quantify their differences. Given maps of the same city collected from different sources, researchers often need to know how they differ. Map comparison is very important in the field of transportation network analysis as well as to assess the quality of map construction algorithms. We present a new path-based distance measure to compare two planar geometric graphs that are embedded in the same plane. Our distance measure takes structural as well as spatial properties into account. We show that it can be approximated in polynomial time and it preserves structural and spatial properties of the graphs. We provide experimental results comparing vendor quality street maps (TeleAtlas) with open source maps (OpenStreetMap), as well as maps generated by map construction algorithms with ground-truth maps (OpenStreetMap).
This book focuses on the generalization of map features, providing descriptions and classifying groups of map objects into six categories: point clusters, groups of contours, road networks, river networks, continuous areal features and discrete areal features. Discussing the methods and algorithms in map generalization in equal measure, it also describes the approaches for describing map features. The book is a valuable reference for graduates and researchers who are interested in cartography and geographic information science/systems, especially those in automated map generalization and spatial databases construction.
Computers and automation have revolutionized the lives of most people in the last two decades, and terminology such as algorithms, big data and artificial intelligence have become part of our everyday discourse. This book presents the proceedings of CAIBDA 2023, the 3rd International Conference on Artificial Intelligence, Big Data and Algorithms, held from 16 - 18 June 2023 as a hybrid conference in Zhengzhou, China. The conference provided a platform for some 200 participants to discuss the theoretical and computational aspects of research in artificial intelligence, big data and algorithms, reviewing the present status and future perspectives of the field. A total of 362 submissions were received for the conference, of which 148 were accepted following a thorough double-blind peer review. Topics covered at the conference included artificial intelligence tools and applications; intelligent estimation and classification; representation formats for multimedia big data; high-performance computing; and mathematical and computer modeling, among others. The book provides a comprehensive overview of this fascinating field, exploring future scenarios and highlighting areas where new ideas have emerged over recent years. It will be of interest to all those whose work involves artificial intelligence, big data and algorithms.
This book presents select proceedings of the International Conference on Intelligent Automation and Soft Computing (IASC2021). Various topics covered in this book include AI algorithm, neural networks, pattern recognition, machine learning, blockchain technology, system engineering, computer vision and image processing, adaptive control and robotics, big data and data processing, networking and security. The book is a valuable reference for beginners, researchers, and professionals interested in artificial intelligence, automation, and soft computing.
This volume constitutes the refereed post-conference proceedings of the Third International Conference on Machine Learning and Intelligent Communications, MLICOM 2018, held in Hangzhou, China, in July 2018. The 66 revised full papers were carefully selected from 102 submissions. The papers are organized thematically in machine learning, intelligent positioning and navigation, intelligent multimedia processing and security, wireless mobile network and security, cognitive radio and intelligent networking, IoT, intelligent satellite communications and networking, green communication and intelligent networking, ad-hoc and sensor networks, resource allocation in wireless and cloud networks, signal processing in wireless and optical communications, and intelligent cooperative communications and networking.
Novel Algorithms and Techniques in Telecommunications, Automation and Industrial Electronics includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art research projects in the areas of Industrial Electronics, Technology and Automation, Telecommunications and Networking. Novel Algorithms and Techniques in Telecommunications, Automation and Industrial Electronics includes selected papers form the conference proceedings of the International Conference on Industrial Electronics, Technology and Automation (IETA 2007) and International Conference on Telecommunications and Networking (TeNe 07) which were part of the International Joint Conferences on Computer, Information and Systems Sciences and Engineering (CISSE 2007).
Distributed Computing by Mobile Entities is concerned with the study of the computational and complexity issues arising in systems of decentralized computational entities operating in a spatial universe Encompassing and modeling a large variety of application environments and systems, from robotic swarms to networks of mobile sensors, from software mobile agents in communication networks to crawlers and viruses on the web, the theoretical research in this area intersects distributed computing with the fields of computational geometry (especially for continuous spaces), control theory, graph theory and combinatorics (especially for discrete spaces). The research focus is on determining what tasks can be performed by the entities, under what conditions, and at what cost. In particular, the central question is to determine what minimal hypotheses allow a given problem to be solved. This book is based on the lectures and tutorial presented at the research meeting on “Moving and Computing" (mac) held at La Maddalena Island in June 2017. Greatly expanded, revised and updated, each of the lectures forms an individual Chapter. Together, they provide a map of the current knowledge about the boundaries of distributed computing by mobile entities.
This proceedings focus on selected aspects of recent advances and experiences, emerging technology trends that have positively impacted our world from operators, authorities and associations from around the world to help address the world’s computing, control and industrial engineering. Meanwhile, although the group that studies Computing, Control and Industrial Engineering is very large, the topics included into this proceedings have the extremely high research value. The program chair, speakers, and editors of this conference are well-known person in the industry, and CCIE2021 will also strictly select articles when calling for papers.
While wireless technologies continue to provide an array of new challenges and multi-domain applications for business processes and solutions, there still remains to be a comprehensive understanding of its various dimensions and environments. Security, Design, and Architecture for Broadband and Wireless Network Technologies provides a discussion on the latest research achievements in wireless networks and broadband technology. Highlighting new trends, applications, developments, and standards, this book is essential for next generation researchers and practitioners in the ICT field.